{"id":"W4327568934","doi":"10.1155/2023/7686208","title":"Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanghai Office of Philosophy and Social Science; Jilin Office of Philosophy and Social Science","keywords":"Train; Flow (mathematics); Transport engineering; Scheme (mathematics); Computer science; Megacity; Set (abstract data type); Matching (statistics); Grid; Operations research; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006481749,0.0009313284,0.0009513298,0.0008445925,0.000455952,0.0008097883,0.000967332,0.0006619788,0.001383604],"category_scores_gemma":[0.001069837,0.0004053185,0.0008044526,0.0009573829,0.0003433311,0.001291179,0.0007327425,0.0005145094,0.0001532079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006400391,"about_ca_system_score_gemma":0.001018257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107135,"about_ca_topic_score_gemma":0.008068797,"domain_scores_codex":[0.9996845,0.0000708551,0.00001990791,0.0001106136,0.00007245878,0.00004171455],"domain_scores_gemma":[0.9997212,0.0000989192,0.00005948812,0.00002802759,0.00006772345,0.0000246619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003406339,0.00004868034,0.002079662,0.00005864269,0.00005092095,0.00005450349,0.00009596709,0.9403019,0.002328501,0.003500482,0.0006227641,0.05082394],"study_design_scores_gemma":[0.000002596915,0.00001323944,0.0001968661,0.000001544546,0.000005260472,0.000005873956,0.00001639005,0.9988095,0.0002272797,0.0004762545,0.0002422665,0.000003014699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0340406,0.0001618334,0.9638316,0.00008678136,0.00002069949,0.00005019642,0.00005051558,0.0001551017,0.001602605],"genre_scores_gemma":[0.7689193,0.0002583942,0.2278577,0.00005532478,0.0000326925,0.0001671035,0.0001657993,0.00007832222,0.002465321],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01107135,"threshold_uncertainty_score":0.02201384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128271864046861,"score_gpt":0.3360721278047874,"score_spread":0.3147894091643188,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}